• 한국수학교육학회지시리즈D:수학교육연구
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• 제16권3호
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• pp.155-176
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• 2012

It is an important issue to explore classroom environments which are conducive to developing students' mathematical performance. This study explores the effects of different classroom environments (solution-demand and corresponding-time setting) on mathematical performances. Fourteen and eighteen prospective teachers were required to prove a task under different conditions respectively: a) Cognitive demand of multiple-solution corresponding time of three hours, and b) Cognitive demand of a right solution corresponding time of 20 minutes. We used SOLO as the assessment tool for mathematical performance from quality perspective. Significant differences were found in the quantity and quality of mathematical performance. The regular environment focusing on speed and accuracy were found to be directly linked to low levels of performance. The findings above provide implications to the cognitive benefits of multiple-solution demand and corresponding time setting.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권4호
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• pp.1100-1122
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• 2023

Scheduling user-submitted cloud tasks to the appropriate virtual machine (VM) in cloud computing is critical for cloud providers. However, as the demand for cloud resources from user tasks continues to grow, current evolutionary algorithms (EAs) cannot satisfy the optimal solution of large-scale cloud task scheduling problems. In this paper, we first construct a large- scale multi-objective cloud task problem considering the time and cost functions. Second, a multi-objective optimization algorithm based on multi-factor optimization (MFO) is proposed to solve the established problem. This algorithm solves by decomposing the large-scale optimization problem into multiple optimization subproblems. This reduces the computational burden of the algorithm. Later, the introduction of the MFO strategy provides the algorithm with a parallel evolutionary paradigm for multiple subpopulations of implicit knowledge transfer. Finally, simulation experiments and comparisons are performed on a large-scale task scheduling test set on the CloudSim platform. Experimental results show that our algorithm can obtain the best scheduling solution while maintaining good results of the objective function compared with other optimization algorithms.

• Journal of Information Processing Systems
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• 제17권3호
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• pp.441-452
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• 2021

Federated learning provides an efficient integrated model for distributed data, allowing the local training of different data. Meanwhile, the goal of multi-task learning is to simultaneously establish models for multiple related tasks, and to obtain the underlying main structure. However, traditional federated multi-task learning models not only have strict requirements for the data distribution, but also demand large amounts of calculation and have slow convergence, which hindered their promotion in many fields. In our work, we apply the rank constraint on weight vectors of the multi-task learning model to adaptively adjust the task's similarity learning, according to the distribution of federal node data. The proposed model has a general framework for solving optimal solutions, which can be used to deal with various data types. Experiments show that our model has achieved the best results in different dataset. Notably, our model can still obtain stable results in datasets with large distribution differences. In addition, compared with traditional federated multi-task learning models, our algorithm is able to converge on a local optimal solution within limited training iterations.

• 전자공학회논문지B
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• 제29B권3호
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• pp.6-15
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• 1992

This paper proposes a method for the global optimization of redundancy over the whole task period for a kinematically redundant robot. The necessary conditions based on the calculus of variations for an integral type cost criterion result in a second-order differential equation. For a cyclic task, the periodic boundary conditions due to conservativity requirements are discussed. We refine the two-point boundary value problem to an initial value adjustment problem and suggest a numerical search method for providing the conservative global optimal solution using the gradient projection method. Since the initial joint velocity is parameterized with the number of the redundancy, we only search the parameter value in the space of as many dimensions as the number of degrees of redundancy. We show through numerical examples that multiple nonhomotopic extremal solutions and the generality of the proposed method by considering the dynamics of a robot.

• 제어로봇시스템학회논문지
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• 제10권10호
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• pp.930-939
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• 2004

In this paper, both dynamic constraints and kinematic constraints are considered for the analysis of manipulability of robotic systems comprised of multiple cooperating arms. Given bounds on the torques of each Joint actuator for every robot, the purpose of this study is to drive the bounds of task-space acceleration of object carried by the system. Bounds on each joint torque, described as a polytope, is transformed to the task-space acceleration through matrices related with robot dynamics, robot kinematics, object dynamics, grasp conditions, and contact conditions. A series of mathematical manipulations including the procedure calculating minimum infinite-norm solution of linear equation is applied to get the reachable acceleration bounds from given actuator dynamic constrains. Several examples including two robot systems as well as three robot system are shown with the assumptions of complete-constraint contact model(or' very soft contact') and insufficient or proper degree of freedom robot.

• International Journal of Control, Automation, and Systems
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• 제4권5호
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• pp.601-614
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• 2006

In this paper, a study on task assignment strategies for a complex real-time network system is presented. Firstly, two task assignment strategies are proposed to improve previous strategies. The proposed strategies assign tasks with meeting end-to-end real-time constraints, and also with optimizing system utilization through period modulation of the tasks. Consequently, the strategies aim at the optimizationto optimize of system performance with while still meeting real-time constraints. The proposed task assignment strategies are devised using the genetic algorithmswith heuristic real-time constraints in the generation of new populations. The strategies are differentiated by the optimization method of the two objectives-meeting end-to-end real-time constraints and optimizing system utilization: the first one has sequential genetic algorithm routines for the objectives, and the second one has one multiple objective genetic algorithm routine to find a Pareto solution. Secondly, the performances of the proposed strategies and a well-known existing task assignment strategy using the BnB(Branch and Bound) optimization are compared with one other through some simulation tests. Through the comparison of the simulation results, the most adequate task assignment strategies are proposed for some as system requirements-: the optimization of system utilization, the maximization of running tasktasks, and the minimization of the number of network node nodesnumber for a network system.

• 대한수학교육학회지:학교수학
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• 제16권1호
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• pp.1-17
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• 2014

본 연구의 목적은 한 문제를 다양한 방법으로 해결할 수 있는 문제와 이에 대한 채점방법을 활용하여 학생들의 수학적 창의성을 측정함으로써 수학적 창의성을 측정할 수 있는 기반을 구축하는 것이다. 이를 위해 초등 5학년 학생 10명을 대상으로 다양한 방법으로 해결할 수 있는 문제를 활용하여 검사를 실시하여 수학적 창의성을 측정하였다. 수학적 창의성 측정을 위하여 창의성의 하위 요소인 유창성, 융통성, 독창성을 바탕으로 '새롭고, 가치 있는' 수학적 산출물을 평가할 수 있는 채점방법을 구축하여 활용하였다. 분석 결과, 수학적 창의성 점수는 학생 간 편차가 크게 나타났다. 또한 문항별로도 수학적 창의성 점수에서 차이가 나타나, 수학 학습 내용에 따라 학생들의 수학적 창의성 분석의 필요성이 대두되었다. 본 연구의 채점방법에 따르면, 유창성이 높을수록 수학적 창의성이 높았다. 그렇지만 '새롭고, 가치 있는' 수학적 창의성의 특성을 부각시키는 채점방법에 의해 유창성과 융통성이 증가할수록 답의 희소성이 낮아져 상대적으로 독창성 점수를 얻기가 어려웠다. 따라서 답의 희소성과 수학적인 측면에서 답의 가치를 동시에 고려하는 독창성 판단의 준거를 만들 필요가 대두되었다.

• 한국경영과학회지
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• 제33권3호
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• pp.1-16
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• 2008

This paper considers a scheduling problem to minimize the total tardiness in the two-stage assembly-type flowshop. The system is composed of multiple fabrication machines in the first stage and a final-assembly machine in the second stage. Each job consists of multiple tasks, each task is performed on the fabrication machine specified in advance. After all the tasks of a job are finished, the assembly task can be started on the final-assembly machine. The completion time of a job is the time that the assembly task for the job is completed. The objective of this paper is to find the optimal schedule minimizing the total tardiness of a group of jobs. In the problem analysis, we first derive three solution properties to determine the sequence between two consecutive jobs. Moreover, two lower objective bounds are derived and tested along with the derived properties within a branch-and-bound scheme. Two efficient heuristic algorithms are also developed. The overall performances of the proposed properties, branch-and-bound and heuristic algorithms are evaluated through numerical experiments.

• 로봇학회논문지
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• 제2권1호
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• pp.93-102
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• 2007

It is essential to estimating positions of multiple robots in order to perform cooperative task in common workspace. Accordingly, we propose a new approach of cooperative localization for multiple robots utilizing correlation among GPS errors in common workspace. Assuming that GPS data of individual robot are correlated strongly as the distance among robots are close, it is confirmed that the proposed method provides improved localization accuracy. In addition, we define two operational parameters to apply proposed method in multiple robot system. With mentioned two parameters, we present a practical solution to accumulated position error in traveling long distance.

• 한국정보처리학회논문지
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• 제6권9호
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• pp.2311-2319
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• 1999

병렬 컴퓨팅에 있어 NP-complete 문제인 태스크 할당문제에 대한 두 가지 휴리스틱 알고리즘을 제시한다. 할당문제는 분산 메모리 멀티컴퓨터의 멀티 프로세싱 노드에 다중통신 태스크들을 최적의 매핑을 찾는 것이다. 태스크들을 목표 시스템 구조의 노드들에 매핑시키는 목적은 해법 품질에 손상 없이 병렬 실행시간을 최소화하기 위함이다. 많은 휴리스틱 기법들이 만족한 매핑을 얻기 위해 채택되어 왔다. 본 논문에서 제시되는 휴리스틱 기법은 유전자 알고리즘(GA)과 시뮬레이티드 어닐링(SA) 기법에 기반을 둔다. 매핑 설정을 위한 총 계산 비용으로 목적함수를 수식화하고 휴리스틱 알고리즘들의 성능을 평가한다. 랜덤, 그리디, 유전자, 어닐링 알고리즘들을 사용하여 얻은 해법의 품질과 시간을 비교한다. 할당 알고리즘 시뮬레이션 연구를 통한 실험적 결과를 보여준다.